Systems and methods for generating a data definition language statement

A method for generating a data definition language (DDL) statement for a database management product, the method comprising:

• receiving at an interface a partial DDL text input;
• providing the partial DDL text input to a machine learning model trained by:
• receiving a plurality of sample DDL statements,
• identifying an object type associated with each of the sample DDL statements,
• creating sequences of tokens representing the objects,
• generating a plurality of pairs of the token sequences, wherein each pair includes a first token group and a second token group, and the second token group follows the first token group;
• and
• varying the length of at least one of the first token group and the second token group to determine which sample token would follow a given series of sample tokens;
• and
• wherein the trained machine learning model then:
• analyzes the received partial DDL text input, and
• generates a complete DDL statement based on the analysis of the received partial DDL text input and the plurality of sample DDL statements.

A system for generating a data definition language (DDL) statement for a database management product, the system comprising:

• an interface for at least receiving a partial DDL text input;
• a database for storing a plurality of sample DDL statements;
• one or more processors executing instructions stored on memory and configured to:
• execute a machine learning model trained by:
• receiving the plurality of sample DDL statements,
• identifying an object type associated with each of the sample DDL statements,
• creating sequences of tokens representing the objects,
• generating a plurality of pairs of the token sequences, wherein each pair includes a first token group and a second token group, and the second token group follows the first token group, and
• varying the length of at least one of the first token group and the second token group to determine which sample token would follow a given series of sample tokens;
• wherein machine learning model is configured to:
• analyze the received partial DDL text input, and
• generate a complete DDL statement based on the analysis of the received partial DDL text input and the plurality of sample DDL statements.

A computer program product for generating a data definition language (DDL) statement for a database management product, the computer program product comprising computer executable code embodied in one or more non-transitory computer readable media that, when executing on one or more processors, performs the steps of:

• receiving at an interface a partial DDL text input;
• providing the partial DDL text input to a machine learning model trained by:
• receiving a plurality of sample DDL statements,
• identifying an object type associated with each of the sample DDL statements,
• creating sequences of tokens representing the objects,
• generating a plurality of pairs of the token sequences, wherein each pair includes a first token group and a second token group, and the second token group follows the first token group;
• and
• varying the length of at least one of the first token group and the second token group to determine which sample token would follow a given series of sample tokens;
• and
• wherein the trained machine learning model then:
• analyzes the received partial DDL text input, and generates a complete DDL statement based on the analysis of the received partial DDL text input and the plurality of sample DDL statements.